code: def sum_on_target_divided_by_two(_eval_df, builtin_metrics):
      """
      This example custom metric function creates a metric derived from existing metrics in
      ``builtin_metrics``.
      """
      return builtin_metrics["sum_on_target"] / 2
  
file_path: mlflow/examples/evaluation/evaluate_with_custom_metrics.py
imports: import os
  import matplotlib.pyplot
  import numpy
  from sklearn.datasets import fetch_california_housing
  from sklearn.linear_model import LinearRegression
  from sklearn.model_selection import train_test_split
  import mlflow
  from mlflow.models import infer_signature, make_metric
label_desc: Use image node_id 2 for calling a global function with example usage: sum_on_target_divided_by_two(_eval_df, builtin_metrics) and returns: unknown